Topic: chemical synapses

Neurons in the brain communicate through action potentials (spikes) that are transmitted through chemical synapses. Throughout the last decades, the question how networks of spiking neurons represent and process information has remained an important challenge. Some progress has resulted from a recent family of supervised learning rules (tempotrons) for models of spiking neurons. However, these studies have viewed synaptic transmission as static and characterized synaptic efficacies as scalar quantities that change only on slow time scales of learning across trials but remain fixed on the fast

Recent large-scale community effort has produced comprehensive mapping of neurons and chemical synapses in both the Drosophila larva and adult brains (‘connectomes’). In addition, the neurotransmitter expression of each neuron can be predicted using a machine learning algorithm. However, interpreting connectomics data has proven challenging: most neurons connect to tens/hundreds of upstream/downstream neurons, and removing weak connections eliminates most connections in the brain. This could lead to biassed usage of connectomics data, favouring neurons previously studied, or those accessible w

The nanoscale arrangement of chemical synapses is thought to be critical for establishing synapse strength but whether this arrangement is sensitive to changes in in vivo activity is not known. Pyramidal neurons in the cortex receive a multitude of excitatory and inhibitory inputs that determine the generation of the action potential (AP) at the axon initial segment (AIS). Chandelier cells (ChCs), a GABAergic interneuron subtype, targets the AIS of pyramidal neurons through axo-axonic synapses and is therefore thought to strongly modulate neuronal output. We used super-resolution microscopy (S